Markets entering the close of Q1 earnings season have shown a clear tendency to reward stocks where near-term earnings strength overlaps with larger, persistent growth themes. In recent weeks this has manifested as pronounced rallies among companies positioned to benefit from enterprise AI adoption and the build-out of AI infrastructure. Quantitative, AI-driven strategies have flagged a number of these opportunities ahead of broader recognition, and several of those high-conviction picks have produced double-digit gains in May.
This report details the key names highlighted by the models, the factual drivers the models identified, and the broader mechanics of the selection process. It also notes some inconsistencies in reported month-to-date moves within the underlying source material and reflects those differences rather than attempting to reconcile them.
Key takeaways
- AI and infrastructure-related momentum is accelerating the rotation into stocks with both short-term earnings catalysts and larger secular growth potential.
- Model-driven strategies highlighted several names that recorded double-digit gains in May, including a cloud data and analytics provider, a semiconductor equipment leader and a healthcare technology firm.
- These AI-identified picks were recognized across multiple independent strategies, suggesting a convergent setup rather than a single-model anomaly.
Three high-conviction picks singled out by models
InvestingPro model subscribers received high-conviction calls on several stocks that the models identified across three different strategies. The following firms and the factual details associated with each formed the backbone of the models’ decisions.
Teradata Corp (NYSE:TDC)
Teradata was highlighted for the combination of a near-term earnings beat and a structural transition toward enterprise AI and cloud recurring revenue. The company reported an EPS of $0.88 versus $0.69 expected, and $444 million in revenue, a result that catalyzed the more recent price action. The source material also notes the stock’s strong month-to-date performance in May, although two different May gain figures appear in the material: one reference cites a +13.52% move in May, while another passage references a 15.56% surge in May. Both figures are preserved here to reflect the underlying reporting.
When the quantitative models evaluated Teradata, they isolated a setup the engine described as Undervalued, AI-Driven Cloud Momentum. The factual points the models flagged included:
- One-year performance and financial flexibility: The stock had delivered roughly 22% returns over the prior year, and a large SAP settlement was identified as a source of additional corporate flexibility that could be redeployed toward growth drivers.
- Valuation disconnect: At the start of May the stock was trading near $26, materially below analyst fair value estimates that ranged between $34 and $39, presenting a valuation gap the models interpreted as an attractive entry point.
- Cloud revenue acceleration: Cloud recurring revenue reportedly grew about 15% year-over-year and now comprises nearly half of total revenue, signaling a shift in the company’s revenue mix toward recurring, cloud-based streams. Historic model signals were also tied to a Q4 2025 result in which EPS reached $0.74 against a $0.54 forecast, and management guidance for 2026 free cash flow of $310–330 million was cited.
- Transition to active enterprise AI: The company has been described as moving beyond data storage to an active enterprise AI platform, with 150 enterprise AI engagements completed and the AI Analyst Agent launched on the Microsoft marketplace — developments that the models considered central to its long-term thesis.
IQVIA Holdings (NYSE:IQV)
IQVIA was flagged by the engine not only for a modest recent earnings beat — EPS of $2.90 versus $2.82 expected — but for its strategic push into healthcare technology and AI-enabled workflows. The models identified the setup as Deeply Discounted Growth at an Undemanding Valuation based on the following factual signals:
- Sharp prior-year selloff: The stock had fallen nearly 30% this year according to the material, a pullback the models interpreted as overly punitive relative to IQVIA’s fundamentals.
- Analyst views mentioned in the source: Multiple analysts, including upgrades from Barclays and TD Cowen referenced in the material, were cited as viewing the selloff as overblown.
- Valuation gap: Around $157 per share, the stock was reported to trade nearly 47% below a consensus analyst fair value of approximately $232, creating what the models treated as a rare discounted entry.
- Operational momentum and guidance: The company posted Q4 2025 revenue of $4.4 billion, up more than 10% year-over-year, and management issued 2026 guidance calling for up to $17.4 billion in revenue and EPS between $12.55 and $12.85.
- AI as a growth engine: IQVIA’s new IQVIA.ai platform, powered by NVIDIA technology, was reported to be embedded in the workflows of 19 of the top 20 pharmaceutical companies, an integration the models interpreted as a material growth lever rather than a disruptive threat.
Applied Materials (NASDAQ:AMAT)
Applied Materials was identified as a high-conviction pick centered on the company’s role in building physical AI infrastructure and its aggressive R&D commitments. The source material attributes substantial month-to-date gains in May to a combination of market momentum and structural investments. As with other names, two different May performance figures appear: one section lists a +10.96% May return, while a later passage references a +14.02% surge in May. Both figures are included here verbatim to retain factual fidelity to the material.
The models described the setup for Applied Materials as Momentum, Growth, and Smart Pricing and highlighted these factual elements:
- One-year and index recognition: The stock reportedly returned about 137% over the prior year and had been added to the S&P 100, establishing a backdrop of strong technical momentum.
- Valuation context: The engine identified a reasonable PEG ratio of about 1.2 despite the substantial one-year return, signaling that forward growth expectations could justify the price.
- Projected revenue and earnings momentum: Forward estimates cited in the source indicate revenue growth of around 13% to roughly $32 billion for the current year and ~19% for the following year, with earnings per share expected to rise approximately 29%. Management’s guidance for Q2 2026 revenue was stated as $7.65 billion ahead of the May 14 earnings report.
- AI infrastructure and strategic partnerships: The company’s $5 billion EPIC Center was described as a core R&D hub already tied to partnerships with SK Hynix and Micron, and the material records a subsequent collaboration with TSMC to co-develop next-generation AI chip technology — developments the models considered central to the firm’s role in the AI infrastructure boom.
Other May standouts flagged by the models
Beyond the three primary names above, the material lists additional model-identified picks that recorded notable May gains in the same reporting window. The factual monthly moves cited include:
- Republic Airways Holdings (NASDAQGS:RJET): +25.38% in May alone
- Qnity Electronics Inc (NYSE:Q): +17.46% in May alone
- Alexandria Real Estate Equities (NYSE:ARE): +12.35% in May alone
- Centene Corp (NYSE:CNC): +11.19% in May alone
- NGL Energy Partners LP (NYSE:NGL): +10.64% in May alone
These selections illustrate that the rotation identified by the models is not limited to AI infrastructure and healthcare technology; it spans a range of sectors where model signals and fundamental developments converged to create buyable setups, according to the source material.
Performance and track record cited
The AI-powered ProPicks strategies were reported to have delivered a cumulative return of +183.48% since their launch, outperforming the S&P 500 by +109.30% over the same period. The material specifies that these are real-world numbers recorded since the official launch of the AI models in November 2023.
Subscribers accessing these signals for less than $9 a month reportedly received early calls on the names covered above. The strategies are described as providing not only curated stock lists but also the explicit rationale behind each addition and removal across the strategies.
How the AI stock picker operates - factual mechanics
The source material outlines the mechanics of the proprietary AI system that underpins the model calls. Those operational details include the following factual components:
- Monthly evaluation universe: At the start of each month the system evaluates thousands of global equities.
- Data and models: The engine processes more than 15 years of financial data across over 150 quantitative models, blending historical patterns, valuation signals and forward-looking growth metrics.
- Selection and sizing: The system identifies up to 20 high-conviction stocks per strategy based on projected medium-term upside potential. Strategies are rebalanced monthly - new ideas are added, strong performers may be retained, and stocks that no longer meet criteria are removed. Each strategy uses equal weighting across selected stocks to provide a consistent benchmark for tracking model performance.
What this rotation implies for investors
The factual narrative advanced by the model outputs in the material is that gains can be driven by a mix of near-term earnings surprises and larger structural moves such as investments in R&D, cloud migration, and enterprise AI adoption. The models concurrently search for undervaluation, accelerating fundamentals and strategic positioning tied to long-term trends.
While the material emphasizes that the AI engine flags a diverse set of catalysts across sectors, it stops short of asserting that any specific factor will guarantee future outperformance. The process described is systematic and rule-based, designed to reposition capital toward stocks that meet the models’ criteria as market conditions evolve.
Limitations and reporting note
The underlying reporting contains a small number of inconsistent month-to-date performance figures for some stocks — notably Teradata and Applied Materials — where different passages list different May returns. Both sets of figures have been retained here rather than reconciled to reflect that the original material contains divergent month-to-date numbers.
Beyond those inconsistencies, the article preserves the factual elements reported about earnings, revenue figures, analyst fair value ranges, platform launches, partnerships, guidance and model mechanics without adding interpretation beyond what is explicitly stated in the source material.
Conclusion
As Q1 earnings season winds down, quantitative models that blend earnings signals with structural growth metrics have identified a set of high-conviction opportunities across cloud analytics, healthcare technology and semiconductor equipment. The factual evidence cited for these names includes recent earnings beats, growing cloud revenue, platform rollouts, large R&D investments and strategic partnerships that position the companies for meaningful participation in enterprise AI and AI infrastructure build-out. Subscribers who accessed these AI-driven strategies prior to the broader market re-rating reportedly benefited from the early calls, which in several instances translated into double-digit gains during May.
Investors reviewing the factual record should note that the models aim to systematically surface opportunities where short-term momentum and long-term structural drivers overlap, but the presence of conflicting month-to-date figures in the source material underlines the importance of cross-checking reported performance numbers during active market rotations.